Fast Adaptable Mobile Robot Navigation in Dynamic Environment

TL;DR

This paper presents a novel adaptive navigation scheme for mobile robots in dynamic environments, combining global and local planning to improve speed and path smoothness over existing methods.

Contribution

It introduces a new navigation algorithm integrating A* and VFH for real-time, adaptive, and collision-free robot navigation in evolving environments.

Findings

Faster goal achievement compared to traditional methods

Smoother paths produced during navigation

Effective in environments where other algorithms fail

Abstract

Autonomous navigation in dynamic environment heavily depends on the environment and its topology. Prior knowledge of the environment is not usually accurate as the environment keeps evolving in time. Since robot is continuously evaluating the environment as it proceeds, deciding the optimal way to traverse the environment to get to the goal, computationally efficient yet mathematically adaptive navigation algorithms are needed. In this paper, a navigation scheme for mobile robot, capable of dealing with time variant environment is proposed. This approach consists of a global planner (A*) and local planner (VFH) to assure an optimal and collision-free robot motion. The algorithm is tested both in simulation and experimentation in different environments that are known to result in failures in VFH and ROS navigation stack, for comparison purposes. Overall, the algorithm enables the robot to get to the goal faster and also produces a smoother path while doing so.